Notice Board :

Call for Paper
Vol. 12 Issue 9

Submission Start Date:
September 01, 2025

Acceptence Notification Start:
September 10, 2025

Submission End:
September 20, 2025

Final MenuScript Due:
September 28, 2025

Publication Date:
September 30, 2025
                         Notice Board: Call for PaperVol. 12 Issue 9      Submission Start Date: September 01, 2025      Acceptence Notification Start: September 10, 2025      Submission End: September 20, 2025      Final MenuScript Due: September 28, 2025      Publication Date: September 30, 2025




Volume XII Issue VII

Author Name
Shivani Chouhan, Srashti Thakur
Year Of Publication
2025
Volume and Issue
Volume 12 Issue 7
Abstract
Understanding customer behavior is crucial for businesses aiming to enhance customer satisfaction, predict churn, and deliver personalized experiences. Recent advancements in machine learning (ML) and deep learning (DL) have significantly transformed the way organizations analyze and forecast customer actions across domains such as e-commerce, finance, and social media. This study presents a comprehensive review of contemporary approaches employed to predict and analyze customer behavior using various ML algorithms like Decision Trees, Random Forest, Logistic Regression, Support Vector Machines, Gradient Boosting, Naïve Bayes, and advanced DL models including Long Short-Term Memory (LSTM) and Transformer-based networks. The reviewed works demonstrate the use of large-scale structured and unstructured datasets, applying models for tasks such as churn prediction, sentiment analysis, product recommendation, and trend forecasting.
PaperID
2025/IJTRM/07/2025/45815